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FORLAB

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FORLAB是一个为科学计算提高一些常用函数的Fortran代码库。它更像是一个小工具箱。

FORLAB使用stdlib作为上游包，相比于stdlib，FORLAB是非正式的，它希望成为一个小的脚手架工具。

项目 描述
版本: 1.0.1
作者: FORLAB 贡献者
源码网页: https://github.com/fortran-fans/forlab
API-Doc网页: https://fortran-fans.github.io/forlab/
许可证: _ORLAB在MIT开源许可证下发行.

开始(English README)

获取代码

git clone https://github.com/fortran-fans/forlab.git
cd forlab

支持的编译器

以下编译器在FORLAB的分支上经过测试：

名字 版本 平台 CPU架构
GCC Fortran(MSYS2) 10 Windows 10 x86_64
GCC Fortran 10 Ubuntu x86_64
GCC Fortran 10 MacOS x86_64

使用fortran-lang/fpm构建

Fortran包管理器(FPM)是一个为Fortran而生的包管理器和构建系统。
你可以使用提供的fpm.toml来构建FORLAB：

fpm build
fpm test --list
fpm test <test_name, see `fpm.toml` or list>

可以在你的FPM工程的fpm.toml文件中添加以下的语句，以使用FORLAB：

[dependencies] # or [dev-dependencies] for tests.
forlab = { git="https://github.com/fortran-fans/forlab.git", branch="forlab-fpm" }

API文档

ford API-doc-FORD-file.md  # todo
cd doc && mdbook build

see forlab-API-doc.

有一些API使用的例子被放置在了example文件夹下，你可以使用FPM来运行它们：

fpm run --example --list
fpm run --example <demo_name, see `fpm.toml` or list>

其它信息

Links

  1. keurfonluu/Forlab
    FORLAB原本是由Keurfon Luu主要开发！
  2. stdlib
    Fortran standard library.
  3. Fortran Generics

Fypp

The original intention of developing the multi-precision library(forlab) is to facilitate the user to switch the program accuracy requirements in a timely manner, which is challenging. We use fypp to build a multi-precision forlab. I have to say that fypp has helped us a lot. I learned that the use of code to generate code is called meta-programming. I also think that metaprogramming has great potential, especially for some low-level polymorphic functions and improving the dynamics of statically compiled languages, which is very helpful.
I hope that fypp will get better and better, and that fortran will natively support meta-programming technology in the future.

The problems we encountered

  1. The adaptability of fortran metaprogramming ability is not strong;
  2. Modular development module and setting submodule should best be combined effectively to improve development efficiency.
  3. We don't want forlab to increase its volume unlimitedly. We hope that it can be used in areas where it can achieve value, such as rapid development of fortran automation applets. So we will keep the forlab lightweight, and update and repair it from time to time.
  4. Fpm currently has some problems and pain points when compiling the program (But we are very optimistic about the potential of fpm):
    • Slow compilation speed. (Improvements in this PR: optimize file listing)
    • Cannot manage and distribute fpm packages well now.
  5. Fortran Generics: Due to the lack of more complete generics, certain functions such as multiple precision and multiple array dimensions cannot be implemented now.